Latest AI and machine learning research in surveys for healthcare professionals.
Thermal protection systems (TPS) of space vehicles are designed computationally rather than experimentally. They are validated using ground experiments, but all aspects of the flight cannot be replicated on ground. This ground-to-flight mapping introduces uncertainties which need to be accounted for while designing any thermal protection system. Thus, precise computational models along with unce...
In the past five years, research has shifted from traditional Machine Learning (ML) and Deep Learning (DL) approaches to leveraging Large Language Models (LLMs) , including multimodality, for data augmentation to enhance generalization, and combat overfitting in training deep convolutional neural networks. However, while existing surveys predominantly focus on ML and DL techniques or limited mod...
Virtually all verification techniques using formal methods rely on the availability of a formal specification, which describes the design requiremen...
This paper presents a survey based on Kasunic's survey research methodology to identify the criteria used by Machine Learning (ML) experts to evalua...
Text-to-Image (T2I) models have recently gained significant attention due to their ability to generate high-quality images and are consequently used...
Computational pathology foundation models (CPathFMs) have emerged as a powerful approach for analyzing histopathological data, leveraging self-super...
Extracting sections from clinical notes is crucial for downstream analysis but is challenging due to variability in formatting and labor-intensive n...
Lower-Limb Fractures (LLF) are a major health concern for older adults, often leading to reduced mobility and prolonged recovery, potentially impair...
This survey delves into the realm of Parameter-Efficient Fine-Tuning (PEFT) within the context of Foundation Models (FMs). PEFT, a cost-effective fi...
As Artificial Intelligence (AI) systems become increasingly integrated into various aspects of daily life, concerns about privacy and ethical accoun...
Epidemiological models can aid policymakers in reducing disease spread by predicting outcomes based on disease dynamics and contact network characte...
Neural Radiance Fields (NeRFs) have remodeled 3D scene representation since release. NeRFs can effectively reconstruct complex 3D scenes from 2D ima...
Human Action Recognition (HAR) is a challenging domain in computer vision, involving recognizing complex patterns by analyzing the spatiotemporal dy...
Two modern trends in insurance are data-intensive underwriting and behavior-based insurance. Data-intensive underwriting means that insurers use and...
In recent years, deep neural networks for image inhomogeneity reduction have shown promising results. However, current methods with (un)supervised s...
Face recognition systems (FRS) exhibit significant accuracy differences based on the user's gender. Since such a gender gap reduces the trustworthin...
Hand gesture recognition has become an important research area, driven by the growing demand for human-computer interaction in fields such as sign l...
Monocular Depth Estimation (MDE) is a core task in computer vision that enables spatial understanding, 3D reconstruction, and autonomous navigation....
This study explores the potential of Large Language Models (LLMs) to generate artificial surveys, with a focus on personal mobility preferences in G...
Racial bias in medicine, such as in dermatology, presents significant ethical and clinical challenges. This is likely to happen because there is a s...